Surgical Approaches to Upper Limb Spasticity in Adult Patients: A Literature Review
Bibliographic record
Abstract
Introduction: Spasticity is the main complication of many upper motor neuron disorders. Many studies describe neuro-orthopedic surgeries for the correction of joint and limb deformities due to spasticity, though less in the upper extremity. The bulk of care provided to patients with spasticity is provided by rehabilitation clinicians, however, few of the surgical outcomes have been summarized or appraised in the rehabilitation literature. Objective: To review the literature for neuro-orthopedic surgical techniques in the upper limb and evaluate the level of evidence for their efficacy in adult patients with spasticity. Method: Electronic databases of MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews were searched for English, French as well as Farsi languages human studies from 1980 to July 2, 2020. After removing duplicated articles, 2,855 studies were screened and 80 were found to be included based on the criteria. The studies were then divided into two groups, with 40 in each trial and non-trial. The results of the 40 trial articles were summarized in three groups: shoulder, elbow and forearm, and wrist and finger, and each group was subdivided based on the types of intervention. Results: The level of evidence was evaluated by Sackett's approach. There were no randomized control trial studies found. About, 4 studies for shoulder, 8 studies for elbow and forearm, 26 studies for wrist and finger (including 4 for the thumb in palm deformity), and 2 systematic reviews were found. Around, two out of 40 trial articles were published in the rehabilitation journals, one systematic review in Cochrane, and the remaining 38 were published in the surgical journals. Conclusion: Most surgical procedures are complex, consisting of several techniques based on the problems and goals of the patient. This complexity interferes with the evaluation of every single procedure. Heterogenicity of the participants and the absence of clinical trial studies are other factors of not having a single conclusion. This review reveals that almost all the studies suggested good results after the surgery in carefully selected cases with goals of reducing spasticity and improvement in function, pain, hygiene, and appearance. A more unified approach and criteria are needed to facilitate a collaborative, evidence-based, patient referral, and surgical selection pathway.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".